In recent years, trials to recognize motions of users using various sensors are popularly made. FIG. 1A illustrates a flow of common motion recognition processing using a sensor. First, data of a certain section (referred to as a “time window” below) is extracted from items of continuous sensor data. Next, a statistical amount (referred to as a “feature amount”) or the like which indicates a feature of a motion to be recognized is calculated from the extracted time window data. Further, the type of the motion is determined by checking whether or not the calculated feature amount is larger than, for example, a threshold set in advance by way of comparison and using a pattern recognition method. Hereinafter, performing three types of processing of data extraction, feature amount calculation and motion recognition is collectively referred to as “recognition processing”.
FIG. 1B illustrates recognition processing when, for example, sensor data SD obtained from an acceleration sensor upon “walking” is used. Data WD of a time window TW specified based on a start time ST and an end time ET is extracted from the sensor data SD. For example, feature amounts F1, F2 and F3 are calculated from the extracted data WD. The motion is recognized as a motion A when the calculated feature amount F1 is larger than a threshold a, and is recognized as a motion B when the feature amount F1 is smaller than the threshold a. FIG. 2 illustrates a configuration example of a motion recognizing system which realizes this recognition processing.
In FIG. 2, a sensor data acquiring/storage unit 1 acquires data from a sensor and temporarily stores the data. A time window start/end time setting unit 21 sets a start time and an end time of a time window which is a section from which data is extracted. A time window data extracting unit 22 extracts sensor data of the set time window. A feature amount calculating unit 23 calculates a feature amount of the extracted sensor data. A motion recognizing unit 24 recognizes a motion based on the calculated feature amount.
Patent Literature 1 discloses an example of recognizing a motion using a sensor in this way. Patent Literature 1 discloses performing recognition processing in order of time window setting, data extraction, feature amount calculation and motion recognition using acceleration sensors attached to a person.